Entity Extraction and Sentiment Analysis Enable Talent Analytics for HR Departments

Entity Extraction, Sentiment Analysis, Social Media Analysis

Entity Extraction and Sentiment Analysis for Talent Analytics

Companies Need to Improve Their Hiring and Retention Policies

Companies have a strong motivation to maximize the stability and effectiveness of their work force. Doing so includes meeting the following goals:

  • Reducing churn
  • Hiring the best and most suitable candidates
  • Improving morale and productivity
  • Aligning employees with corporate goals
  • Enhancing the entire workplace experience

As part of this, increasing current employee engagement – particularly for top employees – is a key factor. HR needs novel and effective ways to meet these challenges.

What Is Talent Analytics?

Fortunately, with the on-going shift of HR departments to digital data, they are gaining access to large amounts of data about their employees and prospective hires. This data can be analyzed with sophisticated AI tools to accomplish goals such as:

  • Making the best hiring decisions;
  • Identifying which features of a company’s offerings to employees (e.g., benefits, pay, and career opportunities) are the key drivers of either hiring the best employees or retaining them once hired;
  • Making sure an employee is in the right job for him/her.

Talent Analytics (also frequently known as People Analytics) is the overall term for this data-driven approach: it gives HR departments a very fine-grained view of applicants and employees. Two Text Analytics technologies, Entity Extraction and Sentiment Analysis, are critical to this analysis.

Entity Extraction Helps HR Winnow the Field

Entity Extraction is an AI technology that discovers key concepts in unstructured text data from any kind of source: LinkedIn profiles, resumes, etc. It extracts names of people, places, and organization names. Its strength lies particularly in the fact that it extracts all names, even ones not seen before. It accomplishes this by performing a detailed linguistic analysis of the context surrounding a name looking for clues to a name’s presence.

HR staff can then explore this extracted data using an AI-based predictive analytics tool. For example, such a tool may suggest the success likelihood for a job candidate based on the organizations they are associated with. Or the tool may suggest how closely a job candidate’s profile matches those of the relevant employee pool.

Sentiment Analysis Helps Maximize Productivity of Current Employees

These days HR departments aren’t limited to formal employee surveys to obtain valuable employee feedback. They can, for example, gain insights from internal discussion boards where employees ask for help, raise issues, and otherwise reveal a great deal about their feelings and thinking. Sentiment Analysis, in particular Entity-based Sentiment Analysis, can automatically analyze this feedback and allow HR Departments to understand how their employees feel about specific aspects of their companies, for example, their benefits packages. It will provide important input for a company to continually improve and put the company in the good position where it can show itself responding quickly and effectively to employees’ wishes and concerns. Sincere efforts like this could certainly improve retention.


Talent Analytics is a critical technology in an economy where it is increasingly necessary for companies to make great efforts to hire and retain the best possible employees. Entity Extraction and Sentiment Analysis make important contributions to that effort.